As a distributed, RESTful search and analytics engine, Elasticsearch is a commonly utilized tool for enabling fast searches that support a variety of data-orientated applications. Features such as real-time analytics, scalable search solutions, and multi-tenancy support all play a strong role Elasticsearch’s growing popularity. However, not all users know how to properly monitor Elasticsearch to the point where it can turn data into actionable insight. By knowing the most important aspects of monitoring Elasticsearch, it is much easier to gain complete visibility into the software and ensure your deployment of the tool goes as smoothly as possible.

Elasticsearch Monitoring Tools

The only way to take advantage of Elasticsearch’s capabilities is by using monitoring tools that help oversee your Elasticsearch environment. There are plenty of tools available designed for maintenance purposes, but it is much more productive to focus on data-oriented resources. Tools such as Elastic Monitoring (Formerly Marvel) and ElasticHQ are suitable options for easily viewing performance metrics in real-time and getting a handle on cluster tasks so you can identify trends occurring within your infrastructure. Elastic Curator is another intuitive offering that can be utilized to manage Elasticsearch indices and snapshots.

Elasticsearch Monitoring Plugins

After installing the right monitoring tools, the next step to proper Elasticsearch monitoring is organizing the plugins that pertain to the details of your Elasticsearch environment. Plugins enhance basic Elasticsearch functionality and while many users with Elasticsearch provided an out-of-the-box option for production cases, the best plugins make up for the missing capability. Unfortunately, site plugins are not supported in Elasticsearch 5.0 (due to security risks), but there are still useful plugins you can use for monitoring Elasticsearch clusters. Be sure to investigate the most relevant plugins like Cerebro and Head, then leverage them depending on your specific needs.

Important Elasticsearch Metrics

Once you have your monitoring tools and plugins set up, you can start to organize the Elasticsearch metrics which will pinpoint any issues occurring within your infrastructure. Elasticsearch APIs efficiently capture performance metrics at any time and data points such as cluster health and search/node/indexing performance are all crucial indicators into its operational state. By playing close attention to these metrics, you’ll automatically gain better visibility into Elasticsearch.

Performance Testing

Undergoing continuous performance testing will help maximize your Elasticsearch monitoring efforts. To ensure your configuration methods are running efficiently, you should be consistently measuring areas such as cluster growth and leveraging Elasticsearch’s benchmarking tool (Rally) as a means of measuring the impact of system changes and, ultimately, preventing lackluster performance.

Utilizing doc values and avoiding swapping will help maintain an ideal speed for your environment and by keeping Elasticsearch up-to-date via these strategies, your monitoring initiatives will ensure Elasticsearch is fully optimized and search remains lightning fast for your users.